Field of Invention
The present invention relates generally to networks and devices, and relates more particularly to intelligent, distributed, scalable, and autonomous resource discovery, management, and stitching in compute, storage and networking environments.
Description of the Related Art
As the value and use of information continues to increase, individuals and businesses seek additional ways to process and store information. One option available to users is information handling systems. An information handling system generally processes, compiles, stores, and/or communicates information or data for business, personal, or other purposes thereby allowing users to take advantage of the value of the information. Because technology and information handling needs and requirements vary between different users or applications, information handling systems may also vary regarding what information is handled, how the information is handled, how much information is processed, stored, or communicated, and how quickly and efficiently the information may be processed, stored, or communicated. The variations in information handling systems allow for information handling systems to be general or configured for a specific user or specific use such as financial transaction processing, airline reservations, enterprise data storage, or global communications. In addition, information handling systems may include a variety of hardware and software components that may be configured to process, store, and communicate information and may include one or more computer systems, data storage systems, and networking systems.
As information handling systems provide increasingly more central and critical operations in modern society, it is important that the networks are reliable. One method used to improve reliability is to provide a centralized network management.
One type of information handing system is a large-scale datacenter or multiple cloud clusters. In a large-scale datacenter or multiple cloud clusters, control and management is a difficult task. Control and management includes resource discovery, reservation, monitoring, maintenance, teardown, etc. Centralized control of federation between different aggregate managers is a popular method, for example global environment for network innovations (GENI) deployment. However, such mechanism requires additional external infrastructure. This architecture is not able to scale infinitely due to the computing and access limitations of the control infrastructure. Furthermore, cloud infrastructure, e.g., OpenStack, itself does not address and solve this scalability issue when controlling thousands of nodes in a data center.
FIG. 1 depicts a block diagram of centralized management structure according to prior art embodiments. FIG. 1 shows a datacenter or cloud infrastructure 120 including a plurality of racks 130, 140, 150, 160, 170, 180, and 190. Within this infrastructure there can be a plurality of customers, for example, as shown in FIG. 1, customer 1 192 and customer 2 194. Each customer 192 and 194 can rent space in the data center. For example, customer 1 192 can rent infrastructure 174 and infrastructure 182 and customer 2 194 can rent infrastructure 172 and 184. In the prior art system shown in FIG. 1 a central management 110 is used. Central management performs all the monitoring, resource discovery, resource allocation, maintenance, etc. in the entire datacenter structure 120 including all racks 130, 140, 150, 160, 170, 180, and 190. Having a central management 110 is limiting in the sense that there is a finite, fixed number of racks that can be added to a central management 110. Therefore, the central management system has inherent scalability and manageability limitations.
Accordingly, what is needed is to solve this scalability issue, enabling extending from ten nodes to a million nodes.